/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

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Flow The Psychology Of Optimal Experience

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Biomechanics And Motor Control Of Human Movement

Distributed visual navigation based on neural Q-learning for a mobile robot is studied in this paper. First, a general distributed structure based on the multiple processors for visual navigation is established according to the decomposition of the mobile robot visual navigation task. Second, in terms of the general distributed structure, the local environment description method based on the Peer Group Filtering (PGF) and fuzzy technology is put forward. Third, in each local environment description, a controller based on neural Q-learning is designed to guide the mobile robot navigation. In the last part of this paper, experimental simulations are done to test the effectiveness of the presented distributed algorithm, including the image segmentation, environment description and navigation policy.

Distributed visual navigation based on neural Q-learning for a mobile robot

This paper mainly focuses on signal recovery using neural networks (NN) for digital signal processor (DSP) based infrared gas sensor. Data processing of the infrared gas sensor is discussed in detail, and then, the methods of solving two problems of the data processing are introduced. Finally, experiment results are presented to show the feasibilities and effectiveness of recovering signals using NN. The advantages and challenge of using NN in the infrared gas sensor are also analyzed.

Signal Recovery Using Neural Networks for DSP Based Infrared Gas Sensor

Disasters, either naturally-occurring or man-made, frequently occur. For example, the recent chemical plant explosion on Nov. 13, 2005 at the Jilin Petrochemical Company caused a major environmental catastrophe in the water system of Songhua River. The explosion produced about 100 tonne of toxic chemicals, including benzene, spilled into the Songhua River and created an 80 km slick. The river contamination forced the shutdown of water supply in Harbin, a city located downstream with 3.8 million residents. The water pollution also brought problems to cities in China and Russia further downstream. Shortly afterwards, on Dec. 17, 2005, the City Central Hospital in Liaoyuan, Jilin Province, caught fire and left 39 people dead. In 2005, several serious coal mine disasters happened in China, which caused great losses in both life and economic assets. The lack of work safety and poor management has led to the high frequency of such coal mine accidents in recent years in China. In addition to the above disasters, there are other emergencies such as the Severe Acute Respiratory Syndrome (SARS), mad-cow disease and bird flu that caused world-wide attention and resulted in huge economic losses. Societal security has been a very important topic for civilians, governments, officials, and researchers as well.

Design of an emergency prediction and prevention platform for societal security decision support using neural networks

In this paper, a motion controller for a pan-tilt camera mounted on an autonomous helicopter is presented. The motion planner is designed according to the kinematics of the pan-tilt camera. However, the solution of the inverse kinematics of the pan-tilt camera is not unique. To deal with this situation, a decision maker is designed. The decision maker makes use of a cost function to decide which solution should be chose. And the error signal is defined as the difference between pan-tilt joint angles and the desired joint angles. The dynamics of the error system is derived, and proportional controllers are designed according to the error dynamics to control the pan and tilt joints respectively. This system is validated in a virtual reality environment, and the simulation results show that this system can track the target successfully.

A motion controller for a pan-tilt camera on an autonomous helicopter

In this paper, we propose a new computer aided diagnosis method of pulmonary nodules in X-ray CT images to reduce false positive (FP) rate under high true positive (TP) rate conditions. An essential core of the method is to extract and combine two novel and effective features from the raw CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a Gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, a principal component analysis technic and any pattern recognition technics such as neural network approaches can then used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method.

Zeng-Guang Hou

Papers

Distributed visual navigation based on neural Q-learning for a mobile robot

Signal Recovery Using Neural Networks for DSP Based Infrared Gas Sensor

Design of an emergency prediction and prevention platform for societal security decision support using neural networks

A motion controller for a pan-tilt camera on an autonomous helicopter

Shape features extraction from pulmonary nodules in X-ray CT images